JCSDA 12 th Annual Technical Review Meeting and Science Workshop on Satellite Data Assimilation

1. JCSDA 12th Annual Technical Review Meeting and Science Workshop on Satellite Data Assimilation Overview of (some of) NESDIS Contributions to the JCSDA Presented by Sid Ahmed Boukabara Senior Data Assimilation Scientist, NESDIS/STAR • Contributions from: • NOAA NESDIS teams (DRT, JPSS/GOES-R PG), and JCSDA External Research Program (FFO)

2. Introduction • NESDIS does not run a data assimilation system in real-time • Strong interest in Accelerating/Optimizing use of satellite data • NESDIS funds multiple projects that impact satellite data assimilation • Approach: • Develop Tools needed to facilitate the use of satellite data • CLBLM, CRTM & CSEM • Satellite Data Thinning & Representation Optimization • CMFT Centralized BUFRization Tool • General Satellite QC Tool (MIIDAPS) • Accelerate/Optimize use of satellite data • OSCAT, GPM, ATMS, SSMIS, GOES-R, Etc • Proxy data for day-1 readiness • Advance DA Science to allow more satellite data to be used (cloudy/rainy, ..) • Reach out to external research community • Proving ground & Risk Reduction Programs • FFO • Visiting Scientists, Etc • O2R Environment (S4 and JIBB Support and Upgrade) • Work closely with NWS through directed research for R2O

3. O2R and Engaging the Community Introduction Accelerating/Optimizing Use of Satellite Data Facilitating Using Satellite Data (Community Tools) 4 1 3 2 Contents

4. CRTM • CRTM Mission • Satellite radiance simulation and assimilation for passive MW, IR, & Visible sensors of NOAA,NASA,DoD satellites, and others (200 sensors) • Simulation of clear/cloudy/precipitating scenes, globally • CRTM Applications • Data assimilation in supporting of weather forecasting • Physical retrieval algorithm for products • Stability and accuracy monitoring of satelliteobservations • Education and Research: reanalysis, climate studies, air quality forecasting, and a radiative tool for students • CRTM Future Development • Acquarius, SMOS, SMAP, .. • CRTM for CMAQ • CRTM unapodized capability • CRTM for cloudy/rainy data assimilation ATMS Ch. 4 (O-B) GDAS (slide based on Q. Liu presentation)

5. CLBLM • An effort has been initiated to modernize the LBLRTM. Collaborative work between JCSDA and AER. • Features of CLBLM • Modern coding standards • Streamlined Interface (inputs, outputs and spectroscopy) • Modular • Easy to maintain and upgrade • Parallel processing • For all spectral regions • Status: • Design/Planning Phase • LBLRTM de-coding • Early stage of implementation

6. CSEM: Community Surface Emissivity Model For all Spectral regions and for all surface types Combination of models, LUTs, empirical Centralizes all developments for the JCSDA emissivity effort Fully Integrated with CRTM Summary and Plans available. Feedback and suggestions welcome Sea Ice Snow Ocean Canopy Desert (slide from M. Chen & F. Weng)

7. 1DVAR Pre-Processing (MIIDAPS) • Efforts are on going to: • Use 1DVAR as a pre-processor to NWP for quality control purposes • QC of satellite data, rain and ice detection, coast contamination, • RFI for imagers, etc) • based on MiRS technology (significant leverage) • Implement dynamically-retrieved emissivity in the NWP to allow assimilation of surface –sensitive channels • Assess assimilating sounding products in cloudy/rainy conditions Points Passing QC O-A(MIIDAPS) Bias: -0.2 StdDev: 0.43 O-A(Oper.) Goal is to have a community QC tool for satellite data assimilation pre-processing: extend the MIIDAPS to all Sensors (IR & MW, geo/Pol) (slide courtesy of K. Garrett)

8. Community Satellite data Thinning and Representation Optimization Tool (CSTROT) • Thinning & Representation is an important aspect of assimilating satellite data • An effort is on-going to optimize this aspect through a standalone tool (CSTROT) • Features include: • Different representations (superobing / sampling) • Variability based thinning • Flexible (sampling rate) • Applicable to different observations • The tool could also serve as a super-sampling tool for ROI (for regional data assimilation) (Effort led by T. Zhu)

9. CMFT: Community Multi-Format Tool • Part of the O2R environment • For Researchers who do not have access to BUFR files. • It is NOT a new tool. • It is instead a tool that centralizes all BUFR formatting kits that exist in a single, user-friendly tool for researchers to use. • Works from many input formats (HDF, ncdf, etc) • Outputs are in BUFR format (WMO flavor and NCEP flavor of BUFR) • Packaged to be user-friendly (GUI), but also applicable to operations (the GUI generates scripts that can run operationally) • Being extended to AMSR-2, GPM, etc The list of data CMFT can process: AMSUAAMSUBMHSSSMISGPSROSNPP ATMSSNPP CRIS MLSOMIHIRS3HIRS4TRMM/TMI Super TMI Etc..

10. O2R and Engaging the Community Introduction Accelerating/Optimizing Use of Satellite Data Facilitating Using Satellite Data (Community Tools) 4 1 3 2 Contents

11. GPM Data Assimilation in JCSDA • JCSDA is an early adopter of the GPM (GMI) data: • Close interaction with GPM science team before launch • High on priority list of the JCSDA executive team (tracked action item) • Listed in the FY14 Directed research activities • Status: • BUFRization of the L1B and L1C complete (for testing purposes) • Close coordination with GMAO on-going • NOAA-NASA MOU in progress to coordinate on cloudy radiance assimilation • Future Steps: • Assessment of GPM/GMI data on GSI/GFS • Assessment of GPM/GMI on GSI/HWRF • Continued coordination with NASA/GMAO • Close interaction with NWS/NCEP on GPM data assimilation transition to NCEP GSI • Assess GPM data impact in active regions (Rain, ice, cloud) (slide courtesy of E. Jones)

12. OSCAT Data Assimilation a • Effort has led to parallel testing of OSCAT DA in the next version of the GDAS system • Both NESDIS and KNMI OSCAT data were investigated • Pre-assessment was done characterize filtering, thinning, biases and observation error • Errors in wind direction was found to have a bigger effect on A/C than intensity • OSCAT has since failed in orbit • Lessons learned will apply to ASCAT and other scatt. data b Impact assessment of the OSCAT scatterometer data assimilation. These plots represent the forecast impact (b) and verification results (a) of OSCAT winds experiments. They represent the change in anomaly correlation and RMS (increase or decrease) of the surface wind speed at 0.995 sigma level. The impact, globally, at 48 hours lead time is mixed, but overall positive. Plot courtesy of Li Bi, Riverside Inc, JCSDA Active Sensors data assimilation scientist. (slide courtesy of L. Bi)

13. AMSR-2 Data Assimilation Land and Atmospheric Activities • JCSDA is actively working on assimilating AMSR-2 data: • Close interaction between NOAA Scientists • Listed in the FY14 Directed research activities • Land applications (soil moisture) • Atmospheric Application (moisture) • Status: • Soil moisture data from AMSR-2 combined with other sensors producing SM • Impact assessment performed • Moisture profiling information content assessed • Future Steps: • Assessment of GPM/GMI data on GSI • Continued coordination with NASA/GMAO • Close interaction with NWS/NCEP on GPM data assimilation transition to NCEP GSI trunk GFS: Without AMSR2 Soil Moisture DA GFS-EnKF: After AMSR2 Soil Moisture DA AMSR2 Soil Moisture (Reference) Assessment of the vertical moisture information content in AMSR-2 data, showing tropospheric sounding capability, prior to assessing the impact in a GSI environment. Assimilation of Satellite Soil Moisture Product from AMSR2 in NCEP Global Forecast System. M. Ek (NCEP) and Zhan (NESDIS). JCSDA Directed research funded project. This effort is JCSDA-facilitated. In this figure, the Noah LSM multiple year means and standard deviations are used to scale the surface layer soil moisture retrievals before assimilation (courtesy K. Garrett, M. Ek, X. Zhan)

14. AMV Data Assimilation Activities • A coordinated AMV Data Assimilation effort is being initiated in the JCSDA through coordination between NESDIS, NWS, Navy, NASA and U. Wisconsin • Goal: • Maximize the impact of AMV in NOAA systems • Learn from Navy/NASA experience using AMVs • R2O transition of academia projects that were proven to offer added value • Prepare for AMV from future sensors (Himawari-8, GOES-R) • Status: • 2 Inter-agency agreements (IAAs) (NOAA-NASA, NOAA-Navy) being routed for approval • Grant proposal already submitted by UW (to leverage previously funded projects) • Assessment of the AMV data being digested in GSI –on going in NESDIS- Unfiltered Filtered (slide courtesy of E. Maddy)

15. O2R and Engaging the Community Introduction Accelerating/Optimizing Use of Satellite Data Facilitating Using Satellite Data (Community Tools) 4 1 3 2 Contents

16. O2R/R2O Environment Scientific efforts in satellite DA in research community • Goal: Accelerates the use of satellite data in NWP centers • How: Build a solid O2R environment for a successful R2O • Ensures resources are in place: supercomputer –S4&JIBB-, a software integration team, etc. • Operations-consistency • Both JIBB and S4 are scheduled to be upgraded • In progress: • Extension of O2R to include Ocean DA (NCODA, HYCOM) • Extension of O2R to include Land Systems (LIS). • Extension of O2R to include NAM Diverse R&D activities Scientific efforts in satellite DA in academia, CIs Scientific efforts in satellite DA funded by partner agencies More than ~ 50 users on both JIBB and S4 (total more than ~100). Mixture of NOAA and Researchers JCSDA’s own DA Activities Select projects for Transition NWP Operational Centers Objective: Improvements in Forecast skills Ongoing Baseline Improvement in NWP centers Example of S4 Disk Space Usage%

17. Mid-Upper Trop Mid-Upper Trop Mid-Upper Trop Mid-Upper Trop Spectroscopy Mean residuals from 36 AIRS ARM TWP cases using Tobin et al. best estimate sonde profiles CO2 v3 CO2 v2 Previous version (2006) • No P/R line cpl • HITRAN 2000 CO2 parameters Latest version (2011) • P, Q and R line coupling • Lamouroux et al. widths and line coupling • Tashkun positions, intensities • Updated CO2 and H2O continua Improved agreement (Obs - Calc) and consistency across spectral bands! (slide courtesy of V. Payne, formerly AER Inc.)

18. Impacts of ATMS on Track Forecast of Hurricane Sandy SAT SAT+ATMS October 2012 23 24 25 26 27 28 29 (slide courtesy of F. Weng.)

19. Supporting the JCSDA External Research Selected Projects through the NOAA Federally-Funded Opportunity (FFO) –FY13 The FY15 External Research Opportunity target time: Sept-Oct 2014. Status: Identification of gaps and priorities.

20. Questions?